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Schema Markup Extractor

This schema markup extractor fetches any URL and pulls out all the structured data in its HTML: JSON-LD blocks, microdata and RDFa, plus Open Graph and Twitter tags. A summary table lists every item with its type and name, the properties Google requires that are missing, and the recommended ones worth adding. Compare up to 10 URLs side by side, or paste HTML from a page behind a login. Copy any block as JSON-LD or microdata, open it in the matching generator, or download everything as JSON or CSV. SEOs use it to see what markup competitors publish, and developers use it to check a deployment. It reads the HTML as served, so markup added later by JavaScript is not visible to it.

Always freeNo sign upRuns in your browser

How to use

01

Extract a page

Paste a URL and press Extract schemas, paste page HTML, or list up to 10 URLs under Compare. The tool reads JSON-LD, microdata and RDFa, and reports any JSON-LD that is not valid JSON.

02

Read the summary table

Check each item's type and name, the Missing (required) and Recommended to add columns, and the Open Graph and Twitter tab. Filter the blocks below by format.

03

Copy, download or test

Copy a block as JSON-LD or microdata, press Edit to open it in a generator, download JSON or CSV, or use Test live URL to run the page through Google's Rich Results Test.

Why Schema Markup Extractor

How to research competitor schema with the extractor

Structured data is public, so you can see exactly what pages that rank above you publish. A short routine is enough to find gaps. Repeat it every few months, since competitors change their markup too.

  • Search for the query you care about and note the top three to five organic URLs.
  • Paste them into Compare up to 10 URLs, add your own page, and download the Comparison CSV.
  • Compare the types: if every competitor has Product with offers and reviews and you only have WebPage, that is the gap.
  • Open the raw blocks and note optional properties they fill, such as author url, gtin or shippingDetails.
  • Check the Missing (required) column on your own page and fix those first.
  • Press Edit on an item to open the matching generator, paste its code into Import existing JSON-LD, improve it, then extract your page again after publishing.

Common schema types and what Google does with them

When you extract a page you will usually see some of these types. The table shows whether Google uses each for a search feature.

Types without a Google feature can still help other search engines and AI tools understand the page, so finding them is not a mistake. Just do not expect them to change your listing in Google.

Type foundGoogle search feature
OrganizationLogo and company details
WebSiteSite name in results
BreadcrumbListBreadcrumb trail on desktop results
Article, BlogPosting, NewsArticleArticle results
Product with OfferProduct snippets and merchant listings
LocalBusiness and subtypesBusiness details
VideoObjectVideo results and key moments
JobPostingGoogle for Jobs
EventEvent results for in-person events
RecipeRecipe results and carousels
Review, AggregateRatingReview snippet stars
FAQPage, HowToNone: Google no longer shows these
WebPage, AboutPage, ContactPage, CollectionPageNone on their own

Common questions

What does the schema markup extractor pull from a page?
Every JSON-LD script, every top-level microdata item (itemscope without itemprop) and every top-level RDFa item (typeof without property) in the HTML the server returns. Each block is shown formatted, and the summary table lists each entity it contains.
Does the extractor read microdata and RDFa as well as JSON-LD?
Yes. Microdata is read from itemscope, itemtype and itemprop attributes, and RDFa from typeof, property and resource. Both are converted to JSON-style objects so you can compare them with JSON-LD.
What do Missing (required) and Recommended to add mean in the extractor?
Missing lists properties Google requires for that type that the item lacks, such as thumbnailUrl for a VideoObject, plus format errors such as a date that is not ISO 8601. Recommended to add lists properties Google suggests. Each block also has a full validation list. Run important pages through the Rich Results Test as well.
Can the extractor see schema injected by a tag manager?
No. It reads the HTML as served, so markup added by JavaScript after the page loads does not appear. Google can often render JavaScript markup, so use Test live URL to see what Google finds.
Can I download extracted structured data?
Yes. Download JSON saves the URL with separate jsonLd, microdata, rdfa and meta arrays. Summary CSV saves the table of formats, types, names, missing and recommended properties. In Compare mode, Comparison CSV puts every URL's items in one file.
How do I use the schema extractor for competitor research?
Extract the pages that rank for a query you care about and compare their summary tables. Look at which types they publish and which optional properties they fill. The section below lists the steps.
Why does the extractor find no structured data on a page I know has markup?
Usually because the markup is added by JavaScript, the site blocks automated requests, or the markup is on a different version of the URL, such as www or a trailing slash. Try the exact canonical address.
What does it mean when a JSON-LD block has invalid JSON?
The script could not be parsed, often because of a trailing comma, an unescaped quote or a template tag that did not render. Search engines skip a block like that entirely, so fix the source template.
Can I extract schema from several URLs at once?
Yes, up to 10. Open Compare up to 10 URLs, paste one URL per line and press Extract all. A table shows each URL's types, error count and warning count, Show details opens any one of them, and Comparison CSV downloads all the items.
Can I extract schema from a page behind a login?
Yes. Open the page in your browser, view the source, copy it and paste it into the Paste HTML tab. The HTML is read in your browser and not uploaded, and you get the same summary, validation and social tags.

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